Jeffrey L. McKinstry

2.6k citations

17 papers · 1.2k indexed · 2 hit papers · h-index 10

Cognitive Neuroscience top 5%
- Neural dynamics and brain function 11
- Visual perception and processing mechanisms 5
- EEG and Brain-Computer Interfaces 3
Electrical and Electronic Engineering top 5%
- Advanced Memory and Neural Computing 6
Artificial Intelligence top 5%
- Neural Networks and Applications 3
- Domain Adaptation and Few-Shot Learning 2
Cellular and Molecular Neuroscience top 10%
- Neuroscience and Neural Engineering 3
Computer Vision and Pattern Recognition top 5%
- Advanced Neural Network Applications 2

Co-authors: Dharmendra S. Modha David Van Den Berg Myron Flickner Brian Taba Arnon Amir Alexander Andreopoulos Carmelo di Nolfo Rathinakumar Appuswamy
Cited by: Cognitive Neuroscience Electrical and Electronic Engineering Artificial Intelligence
Journals: Proceedings of the National Academy of Sciences (2 papers)Nature Communications (1 paper)PLoS ONE (1 paper)
Partner nations: United States Switzerland Italy

In The Last Decade

Jeffrey L. McKinstry

17 papers receiving 1.2k citations

Hit Papers

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What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

2017 A Low Power, Fully Event-Based Gesture Recognition System
2016 Proceedings of the National Academy of Sciences

Peers

Countries citing papers authored by Jeffrey L. McKinstry

Since Specialization

Citations

This map shows the geographic impact of Jeffrey L. McKinstry's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jeffrey L. McKinstry with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeffrey L. McKinstry more than expected).

Fields of papers citing papers by Jeffrey L. McKinstry

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey L. McKinstry. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jeffrey L. McKinstry. The network helps show where Jeffrey L. McKinstry may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jeffrey L. McKinstry, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jeffrey L. McKinstry Line = papers co-authored together Jeffrey L. McKinstry links everyone, so they are left out of the graph.

All Works

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17 of 17 papers shown

#	Work
1	LEARNED STEP SIZE QUANTIZATION International Conference on Learning Representations ·Steven K. Esser,Jeffrey L. McKinstry,Deepika Bablani,Rathinakumar Appuswamy,Dharmendra S. Modha	2020	38
2	Discovering Low-Precision Networks Close to Full-Precision Networks for Efficient Inference Jeffrey L. McKinstry,Steven K. Esser,Rathinakumar Appuswamy,Deepika Bablani,John V. Arthur,Izzet B. Yildiz,Dharmendra S. Modha	2019	21
3	A Low Power, Fully Event-Based Gesture Recognition Systembreakdown → Arnon Amir,Brian Taba,David Van Den Berg,Timothy Melano,Jeffrey L. McKinstry,Carmelo di Nolfo,Tapan K. Nayak,Alexander Andreopoulos,Guillaume Garreau,Marcela Mendoza,Jeff Kusnitz,Michael DeBole,Steve K. Esser,Tobi Delbrück,Myron Flickner,Dharmendra S. Modha	2017	559
4	Spontaneous emergence of fast attractor dynamics in a model of developing primary visual cortex Nature Communications ·Thomas Miconi,Jeffrey L. McKinstry,Gerald M. Edelman	2016	16
5	Imagery May Arise from Associations Formed through Sensory Experience: A Network of Spiking Neurons Controlling a Robot Learns Visual Sequences in Order to Perform a Mental Rotation Task PLoS ONE ·Jeffrey L. McKinstry,Jason Fleischer,Yanqing Chen,W. Einar Gall,Gerald M. Edelman	2016	6
6	Convolutional networks for fast, energy-efficient neuromorphic computingbreakdown → Proceedings of the National Academy of Sciences ·Steven K. Esser,Paul Merolla,John V. Arthur,Andrew S. Cassidy,Rathinakumar Appuswamy,Alexander Andreopoulos,David Van Den Berg,Jeffrey L. McKinstry,Timothy Melano,Davis Barch,Carmelo di Nolfo,Pallab Datta,Arnon Amir,Brian Taba,Myron Flickner,Dharmendra S. Modha	2016	482
7	Temporal sequence learning in winner-take-all networks of spiking neurons demonstrated in a brain-based device Frontiers in Neurorobotics ·Jeffrey L. McKinstry,Gerald M. Edelman	2013	9
8	Versatile networks of simulated spiking neurons displaying winner-take-all behavior Frontiers in Computational Neuroscience ·Yanqing Chen,Jeffrey L. McKinstry,Gerald M. Edelman	2013	14
9	Charting out the octopus connectome at submicron resolution using the knife-edge scanning microscope BMC Neuroscience ·Yoonsuck Choe,Louise C. Abbott,Giovanna Ponte,John Keyser,Jaerock Kwon,David Mayerich,Daniel E. Miller,Donghyeop Han,Anna Grimaldi,Graziano Fiorito,David B. Edelman,Jeffrey L. McKinstry	2010	6
10	Embodied models of delayed neural responses: Spatiotemporal categorization and predictive motor control in brain based devices Neural Networks ·Jeffrey L. McKinstry,Anil K. Seth,Gerald M. Edelman,Jeffrey L. Krichmar	2008	11
11	Testing for Machine Consciousness Using Insight Learning. National Conference on Artificial Intelligence ·Catherine Marcarelli,Jeffrey L. McKinstry	2007	2
12	A cerebellar model for predictive motor control tested in a brain-based device Proceedings of the National Academy of Sciences ·Jeffrey L. McKinstry,Gerald M. Edelman,Jeffrey L. Krichmar	2006	40
13	Active Sensing of Visual and Tactile Stimuli by Brain-based Devices International Journal of Robotics and Automation ·Anil K. Seth,Jeffrey L. McKinstry,G M Edelman,Jeffrey L. Krichmar	2004	15
14	Texture discrimination by an autonomous mobile brain-based device with whiskers Anil K. Seth,Jeffrey L. McKinstry,Gerald M. Edelman,Jeffrey L. Krichmar	2004	17
15	Self-organizing map develops V1 organization given biologically realistic input Proceedings of International Conference on Neural Networks (ICNN'97) ·Jeffrey L. McKinstry,Clark C. Guest	2002	2
16	Long range connections in primary visual cortex: a large scale model applied to edge detection in gray-scale images Jeffrey L. McKinstry,Clark C. Guest	2002	2
17	A model of primary visual cortex: from single cells to feature maps Jeffrey L. McKinstry,Clark C. Guest	1999	1

About Jeffrey L. McKinstry

Jeffrey L. McKinstry is a scholar working on Cognitive Neuroscience, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 17 papers that have together received 1.2k indexed citations. Recurring topics across this work include Neural dynamics and brain function (11 papers), Advanced Memory and Neural Computing (6 papers), Visual perception and processing mechanisms (5 papers), Neuroscience and Neural Engineering (3 papers), Neural Networks and Applications (3 papers), EEG and Brain-Computer Interfaces (3 papers), Advanced Neural Network Applications (2 papers) and Domain Adaptation and Few-Shot Learning (2 papers). The work is most often cited by research in Cognitive Neuroscience (530 citations), Electrical and Electronic Engineering (924 citations) and Artificial Intelligence (450 citations). Jeffrey L. McKinstry has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Dharmendra S. Modha, David Van Den Berg, Myron Flickner, Brian Taba, Arnon Amir, Alexander Andreopoulos, Carmelo di Nolfo, Rathinakumar Appuswamy, Steven K. Esser and Gerald M. Edelman. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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